FUZZY RELATIONAL MODEL WITH 3-D STRUCTURAL INFORMATION OF OBJECTS

An approarch is proposed that gets a fuzzy relational model of objects by taking 3-D geometrical information of objects obtained from stereo vision as inouts. To solve the scale problem occurred in quantitative representation of 3-D structural information of obiects and lower the matching cost, a fuzzy relational description language (FRDL) is defined in this paper that represents the 3-D geometrical relations of surface pairs of objects qualitatively. By FRDL, the quantitative values of 3-D information of objects could be smoothly tranformed into qualitative values without losing the 3-D information of objects largely. This FRDL also serves as the intermediate description between the quantitative geometric values symbolic description utilized in the machine learning process. With concept learning method, such fuzzy relational model can be generalized and a fuzzy-based 3-D generic model of objects can be learned. Some examples of object houses show the effectiveness of proposed methods. 1